A1 Journal article – refereed

Sleep and cardiometabolic risk: a cluster analysis of actigraphy-derived sleep profiles in adults and children

List of Authors: Matricciani Lisa, Paquet Catherine, Fraysse Francois, Grobler Anneke,Wang Yichao, Baur Louise, Juonala Markus, Nguyen Minh Thien, Ranganathan Sarath, Burgner David, Wake Melissa, Olds Tim


Place: Oxford

Publication year: 2021

Journal: Sleep

Journal name in source: SLEEP

Journal acronym: SLEEP

Volume number: 44

Issue number: 7

Number of pages: 11

ISSN: 0161-8105

eISSN: 1550-9109

DOI: http://dx.doi.org/10.1093/sleep/zsab014


Study objectives: Sleep plays an important role in cardiometabolic health. Although the importance of considering sleep as a multidimensional construct is widely appreciated, studies have largely focused on individual sleep characteristics. The association between actigraphy-derived sleep profiles and cardiometabolic health in healthy adults and children has not been examined.

Methods: This study used actigraphy-measured sleep data collected between February 2015 and March 2016 in the Child Health CheckPoint study. Participants wore actigraphy monitors (GENEActiv Original, Cambs, UK) on their nondominant wrist for 7 days and sleep characteristics (period, efficiency, timing, and variability) were derived from raw actigraphy data. Actigraphy-derived sleep profiles of 1,043 Australian children aged 11-12 years and 1,337 adults were determined using K-means cluster analysis. The association between cluster membership and biomarkers of cardiometabolic health (blood pressure, body mass index, apolipoproteins, glycoprotein acetyls, composite metabolic syndrome severity score) were assessed using Generalized Estimating Equations, adjusting for geographic clustering, with sex, socioeconomic status, maturity stage (age for adults, pubertal status for children), and season of data collection as covariates.

Results: Four actigraphy-derived sleep profiles were identified in both children and adults: short sleepers, late to bed, long sleepers, and overall good sleepers. The overall good sleeper pattern (characterized by adequate sleep period time, high efficiency, early bedtime, and low day-to-day variability) was associated with better cardiometabolic health in the majority of comparisons (80%).

Conclusion: Actigraphy-derived sleep profiles are associated with cardiometabolic health in adults and children. The overall good sleeper pattern is associated with more favorable cardiometabolic health.

Last updated on 2021-02-12 at 13:49